System and method for optimizing waste / recycling collection and delivery routes for service vehicles

ABSTRACT

A system and method for optimizing waste or recycling routes for one or more service vehicles are disclosed. Service providers can determine optimal sets of routes for a fleet of vehicles to traverse in order to service customers more quickly and efficiently. Unique route shapes can be utilized to minimize route overlapping and route balancing can be utilized to produce routes with more manageable daily workloads.

RELATED APPLICATIONS

This application claims the benefit, and priority benefit, of U.S.Provisional Patent Application Ser. No. 63/126,463, filed Dec. 16, 2020,the disclosure and contents of which are incorporated by referenceherein in their entirety.

BACKGROUND 1. Field of Invention

The presently disclosed subject matter relates generally to routeoptimization, and more specifically, to optimization ofcollection/delivery routes for waste/recycling service vehicles.

2. Description of the Related Art

Traditional system and method of waste/recycling operations involvecollecting and transporting waste to disposal stations and delivery ofcontainers to customers by trucks along settled routes. These settledroutes may present logistical and other challenges for serviceproviders. Improvements in this field are therefore desired.

SUMMARY

In accordance with the presently disclosed subject matter, variousillustrative embodiments of a system and method for optimizing waste orrecycling routes for one or more service vehicles are described herein.

In certain illustrative embodiments, a method of optimizing delivery ofwaste or recycling services to customers using a waste or recyclingservice vehicle is disclosed. A sequence is developed of two or morecensus tracts using United States census tract data. A travel route isdeveloped for the waste or recycling service vehicle using the sequenceof two or more census tracts. Waste or recycling services are deliveredto customers along the travel route with the waste or recycling servicevehicle. In certain aspects, the developing of the sequence of two ormore census tracts can include determining a representing stop for eachcensus tract, wherein the representing stop comprises a customerlocation that is at or near the centroid of the census tract, andsequencing the census tracts using the representing stops of each censustract to determine an optimal tract sequence list. In certain aspects,the developing the travel route for the waste or recycling servicevehicle can include: (i) adding all unrouted stops from each censustract into the travel route, starting from the first census tract of theoptimal tract sequence list, until the travel route has met a definedprimary fullness criteria; (ii) adding all unrouted stops from eachcensus block group into the travel route, starting from the first blockgroup of the census tract in (i) that is closest to the census tractthat fulfills the primary fullness criteria, until the travel route hasmet a defined secondary fullness criteria; (iii) adding all unroutedstops from each census block into the travel route, starting from thefirst block of the census block group in (ii) that is closest to thecensus block group that fulfills the primary fullness criteria, untilthe travel route has met a defined tertiary fullness criteria; (iv)determining an optimal sequence for the travel route; and (v) repeatingsteps (i)-(iv) until all desired stops in each census tract are routed.The primary fullness criteria can include one or more of a daily volumecapacity or a daily maximum time met for the travel route. The secondaryfullness criteria can include one or more of a daily volume capacity ora daily maximum time met for the travel route. The secondary fullnesscriteria can vary depending on the type of waste or recycling servicevehicle. The tertiary fullness criteria can include one or more of adaily volume capacity or a daily maximum time met for the travel route.The tertiary fullness criteria can vary depending on the type of wasteor recycling service vehicle. The primary fullness criteria can furtherinclude real time route conditions, including but not limited to trafficconditions on the road, and the position of the vehicle on the roadthrough a GPS device can be applied to perform a real time reroute. Theprimary fullness criteria can further include one or more of the numberof customers already served, and the current customer being servedrelative to the remaining time available to complete the route can beapplied to perform a real time reroute. The secondary fullness criteriafurther can include real time route conditions, including but notlimited to traffic conditions on the road, and the position of thevehicle on the road through a GPS device can be applied to perform areal time reroute. The secondary fullness criteria can further includeone or more of the number of customers already served, and the currentcustomer being served relative to the remaining time available tocomplete the route can be applied to perform a real time reroute. Thetertiary fullness further includes comprises real time route conditions,including but not limited to traffic conditions on the road, and theposition of the vehicle on the road through a GPS device can be appliedto perform a real time reroute. The tertiary fullness criteria furtherinclude one or more of the number of customers already served, and thecurrent customer being served relative to the remaining time availableto complete the route can be applied to perform a real time reroute.

In certain illustrative embodiments, a system for optimizing delivery ofwaste or recycling services to customers is disclosed. The system caninclude a waste or recycling service vehicle, a memory storage area, anda processor in communication with the memory storage area and configuredto develop a sequence of two or more census tracts using United Statescensus tract data, and develop a travel route for the waste or recyclingservice vehicle using the sequence of two or more census tracts. Theprocessor can be further configured to determine a representing stop foreach census tract, wherein the representing stop comprises a customerlocation that is at or near the centroid of the census tract, andsequence the census tracts using the representing stops of each censustract to determine an optimal tract sequence list. The processor can befurther configured to: (i) add all unrouted stops from each census tractinto the travel route, starting from the first census tract of theoptimal tract sequence list, until the travel route has met a definedprimary fullness criteria; (ii) add all unrouted stops from each censusblock group into the travel route, starting from the first block groupof the census tract in (i) that is closest to the census tract thatfulfills the primary fullness criteria, until the travel route has met adefined secondary fullness criteria; (iii) add all unrouted stops fromeach census block into the travel route, starting from the first blockof the census block group in (ii) that is closest to the census blockgroup that fulfills the primary fullness criteria, until the travelroute has met a defined tertiary fullness criteria; (iv) determine anoptimal sequence for the travel route; and (v) repeat steps (i)-(iv)until all desired stops in each census tract are routed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a representative map of U.S. census block, block group, andtract regions according to embodiments of the present disclosure.

FIG. 2 is a diagram of an illustrative method according to embodimentsof the present disclosure.

FIG. 3 is a flow diagram of an illustrative method according toembodiments of the present disclosure.

FIG. 4 is a flow diagram of an illustrative method according toembodiments of the present disclosure.

FIG. 5 is a flow diagram of an illustrative method according toembodiments of the present disclosure.

FIG. 6 is a representative example of a waste services environment to beserviced by a waste service vehicle according to embodiments of thepresent disclosure.

FIG. 7 is a system for data collection and sharing for a waste servicesprovider during performance of a waste service activity in theenvironment of FIG. 1, according to embodiments of the presentdisclosure.

FIG. 8 an example of a communications network for a waste servicesvehicle according to embodiments of the present disclosure.

FIG. 9 is an example of a communications network for a waste servicesvehicle according to embodiments of the present disclosure.

FIG. 10 is an example of a computing system according to embodiments ofthe present disclosure.

While the presently disclosed subject matter will be described inconnection with the preferred embodiment, it will be understood that itis not intended to limit the presently disclosed subject matter to thatembodiment. On the contrary, it is intended to cover all alternatives,modifications, and equivalents, as may be included within the spirit andthe scope of the presently disclosed subject matter as defined by theappended claims.

DETAILED DESCRIPTION

Various illustrative embodiments of a system and method for optimizingwaste or recycling routes for one or more service vehicles are describedherein.

Traditional vehicle routing approaches have sought to minimize thenumber of vehicle routes and total route time and cost for awaste/recycling services provider during performance of a serviceactivity, but these approaches have proven to be ineffective.

In certain illustrative embodiments, the presently disclosed system andmethod can utilize unique route shapes to minimize route overlapping, aswell as utilize route balancing to produce routes with more manageabledaily workloads. The presently disclosed system and method enableproviders to determine optimal sets of routes for a fleet of vehicles totraverse in order to service customers more quickly and efficiently.

In certain illustrative embodiments, the presently disclosed system andmethod can utilize predefined geographic areas such as government censusregions as a guiding tool for vehicle routing. Vehicle routingalgorithms can be developed using nested levels of census geographiessuch as census block identifications. For example, the algorithms canrun up and down to nested levels, e.g., from census tract, to censusblock groups, and to census blocks, which allows a service provider toincorporate more stops into routes while preserving route boundaries. Incertain illustrative embodiments, the presently disclosed system andmethod allow a user to estimate the number of vehicle routes foroperational planning purposes, as well as create an optimal routesequence while considering natural boundaries for tactical planning.

The United States Census Bureau utilizes a census block as a basegeographic unit or region for tabulation of data. Collections of censusblocks form a block group, and collections of block groups form a tract.See FIG. 1 herein. Census blocks can be bounded on all sides by visiblegeographic features, such as streets, roads, streams, and railroadtracks, and can nest within all types of geographic areas. For example,in cities, a census block may correspond to a city block, but in ruralareas where there are fewer roads, census blocks may be defined by otherfeatures such as political boundaries, rivers and other naturalfeatures, parks and similar facilities, etc. Each census block/blockgroup/tract has a unique ID (GEOID). The GEOID for a census block is a15 digit number. A collection of census blocks under same block grouphave the same first 12 digits of the census block ID. Likewise, acollection of block groups sharing the same tract have the same first 11digits of census block group ID.

Referring now to FIG. 2, an illustrative embodiment of a method of usinggeographic entities for vehicle route optimization is provided. Incertain illustrative embodiments, the method can include an iterativetwo-step process.

In Step 1, census tracts are sequenced. In Step 1.1, a customer locationis found that is closest from the centroid of each census tract and thiscustomer stop is set as a representing stop of the census tract. In Step1.2, the census tracts are sequenced using the representing stops ofeach census tract. The output of Step 1.2 is the optimal tract sequencelist (“OTSL”).

In Step 2, routes are created using the OTSL. In Step 2.1, all unroutedstops in the census tract are added into the route, starting from thefirst sequence of the OTSL. In Step 2.2, the route is checked to see ifit is full. As used herein, the term “full” can mean either daily volumecapacity for the route or daily maximum route time met, although otherpossible meanings of the term “full” are also contemplated. When theroute is full by adding all unrouted stops in the current census tract,it is possible that the final sequenced route time is over maximum routetime. In order to increase the level of solution quality both in balanceand in compactness, the next step in the process is to go down to nestedlevels (census block groups and census blocks) of census tract. To doso, if the route is full, first remove recently added stops of thecurrent census tract from the route, and the next set of nested levelscan be applied under Step 2.2.0. If the route is not full, Steps 2.1 and2.2 are repeated with the next sequence of the OTSL. In Step 2.2.0,census block groups of the current census tract can be applied. In Step2.2.1, all unrouted stops in a census block group can be added into theroute, starting from the closest census block group from the previoustract. In Step 2.2.2, the route is checked to see if it is full. If theroute is not full, Steps 2.2.1 and 2.2.2 are repeated with the nextclosest census block group. If the route is full, all stops added in thecurrent census block group are removed, and Steps 2.2.0, 2.2.1, and2.2.2 are repeated with the census block, which is the next nested lowerlevel of the census block group. Once the route is full and no moreblock groups can be added, then Step 2.3 can be applied. In Step 2.3, anoptimal sequence is determined for a given route, and Step 2 is repeateduntil all desired stops in the census tracts are routed.

Referring now to FIG. 3, a more detailed flow diagram of theillustrative embodiment of FIG. 2 is provided.

In certain illustrative embodiments, a method of optimizing delivery ofwaste or recycling services to customers using a waste or recyclingservice vehicle is disclosed. A sequence is developed of two or morecensus tracts using United States census tract data. A travel route isdeveloped for the waste or recycling service vehicle using the sequenceof two or more census tracts. Waste or recycling services are deliveredto customers along the travel route with the waste or recycling servicevehicle. In certain aspects, the developing of the sequence of two ormore census tracts can include determining a representing stop for eachcensus tract, wherein the representing stop comprises a customerlocation that is at or near the centroid of the census tract, andsequencing the census tracts using the representing stops of each censustract to determine an optimal tract sequence list. In certain aspects,the developing the travel route for the waste or recycling servicevehicle can include: (i) adding all unrouted stops from each censustract into the travel route, starting from the first census tract of theoptimal tract sequence list, until the travel route has met a definedprimary fullness criteria; (ii) adding all unrouted stops from eachcensus block group into the travel route, starting from the first blockgroup of the census tract in (i) that is closest to the census tractthat fulfills the primary fullness criteria, until the travel route hasmet a defined secondary fullness criteria; (iii) adding all unroutedstops from each census block into the travel route, starting from thefirst block of the census block group in (ii) that is closest to thecensus block group that fulfills the primary fullness criteria, untilthe travel route has met a defined tertiary fullness criteria; (iv)determining an optimal sequence for the travel route; and (v) repeatingsteps (i)-(iv) until all desired stops in each census tract are routed.The primary fullness criteria can include one or more of a daily volumecapacity or a daily maximum time met for the travel route. The secondaryfullness criteria can include one or more of a daily volume capacity ora daily maximum time met for the travel route. The secondary fullnesscriteria can vary depending on the type of waste or recycling servicevehicle. The tertiary fullness criteria can include one or more of adaily volume capacity or a daily maximum time met for the travel route.The tertiary fullness criteria can vary depending on the type of wasteor recycling service vehicle. The primary fullness criteria can furtherinclude real time route conditions, including but not limited to trafficconditions on the road, and the position of the vehicle on the roadthrough a GPS device can be applied to perform a real time reroute. Theprimary fullness criteria can further include one or more of the numberof customers already served, and the current customer being servedrelative to the remaining time available to complete the route can beapplied to perform a real time reroute. The secondary fullness criteriafurther can include real time route conditions, including but notlimited to traffic conditions on the road, and the position of thevehicle on the road through a GPS device can be applied to perform areal time reroute. The secondary fullness criteria can further includeone or more of the number of customers already served, and the currentcustomer being served relative to the remaining time available tocomplete the route can be applied to perform a real time reroute. Thetertiary fullness further includes comprises real time route conditions,including but not limited to traffic conditions on the road, and theposition of the vehicle on the road through a GPS device can be appliedto perform a real time reroute. The tertiary fullness criteria furtherinclude one or more of the number of customers already served, and thecurrent customer being served relative to the remaining time availableto complete the route can be applied to perform a real time reroute.

In certain illustrative embodiments, a system for optimizing delivery ofwaste or recycling services to customers is disclosed. The system caninclude a waste or recycling service vehicle, a memory storage area, anda processor in communication with the memory storage area and configuredto develop a sequence of two or more census tracts using United Statescensus tract data, and develop a travel route for the waste or recyclingservice vehicle using the sequence of two or more census tracts. Theprocessor can be further configured to determine a representing stop foreach census tract, wherein the representing stop comprises a customerlocation that is at or near the centroid of the census tract, andsequence the census tracts using the representing stops of each censustract to determine an optimal tract sequence list. The processor can befurther configured to: (i) add all unrouted stops from each census tractinto the travel route, starting from the first census tract of theoptimal tract sequence list, until the travel route has met a definedprimary fullness criteria; (ii) add all unrouted stops from each censusblock group into the travel route, starting from the first block groupof the census tract in (i) that is closest to the census tract thatfulfills the primary fullness criteria, until the travel route has met adefined secondary fullness criteria; (iii) add all unrouted stops fromeach census block into the travel route, starting from the first blockof the census block group in (ii) that is closest to the census blockgroup that fulfills the primary fullness criteria, until the travelroute has met a defined tertiary fullness criteria; (iv) determine anoptimal sequence for the travel route; and (v) repeat steps (i)-(iv)until all desired stops in each census tract are routed.

The presently disclosed system and method have a number of advantagesover prior art technologies. Traditionally, vehicle routing has belongedto the NP-hard class of computational complexity theory, meaning it isin a class of problems at least as hard as the hardest problems in NP(non-deterministic polynomial-time). In certain illustrativeembodiments, the presently disclosed system and method are effective fordeveloping well-shaped and well-balanced vehicle routes with minimalroute overlaps, while also minimizing the number of routes and totalroute time. Since census block IDs are based on geographic area andincorporate pre-existing geographic boundaries, the use of this data forfinding routing algorithms and developing solutions and practicalapplications for this information is particularly effective. Forexample, natural geographic barriers such as rivers, mountains, andrailroads can work as route boundaries and be avoided in awaste/recycling collection route. Also, customers in nearby censusblocks are geographically close and thus can be inserted into the sameroute.

The presently disclosed system and method produce well-balanced,well-compacted and well-shaped routes, and also show significant routenumber and total route time savings as compared to existing system andmethod. The resulting routes are balanced with respect to meeting theplanned maximum route time for the routes within an acceptable buffertime. Using the presently disclosed system and method, the number ofroutes whose route time is over a maximum route time plus allowablebuffer is a small percentage and is a significant improvement whileshowing route savings compared to existing systems and methods.

In certain illustrative embodiments, the presently disclosed system andmethod can be extended to using other geographic entities besides U.S.government census regions, such as parcels. For example, the presentlydisclosed system and method can be extended to use parcel geographiesmaintained for the counties in the US, whereby information andattributes of the parcels can be utilized to create routes.

In addition, the presently disclosed system and method can be extendedto using other vehicle routing besides waste/recycling collectionvehicles, such as package delivery/pickup vehicles, food deliveryservices, passenger pickup services, school bus routing, and the like.The vehicle routing solutions provide an accurate estimate of the totalroute time and are designed to minimize the cost of the route whilemeeting the other required constraints and providing consistency ofservice to customers in various types of industries.

Referring now to FIGS. 4-5, illustrative embodiments of a system andmethod for using geographic entities for future route estimation arealso provided. Traditional means for estimating future routes are oftenbased on historical data regarding the number of routes used in relationto the forecasted volume of waste in a specific operational orgeographic area. This typical approach has a number of disadvantages.For example, it does not accurately estimate volume increase/decrease atthe customer level. Also, it cannot project the impact of volumeincrease to route times, especially correlations of landfill breakpoints for a route because of volume changes to estimate the routetimes.

In certain illustrative embodiments, the presently disclosed system andmethod can estimate the number of future routes based on future customerfootprint or anticipated demand, which can lead to more effectiveoperational planning. This approach can be applicable to multiple usecases, including loss or gain of customers because of seasonal volumechanges as well as economic conditions resulting in loss or gain ofcustomers, to inform the anticipated number of future routes. Inaddition, estimating the number of future routes can also anticipatefuture driver and/or vehicle needs to meet operational requirements.

In certain illustrative embodiments, the following steps can be utilizedas an alternative to, or in addition to, using historical volume vs.number of routes. As shown in FIG. 5, for a volume increase of “v %” anda current number of routes of “k”, the route optimization describedherein can be run initially with current volume and current number ofroutes, to determine the current route time maximum. Next, for everycustomer, volume v % can be increased and the route optimization can bere-run with the route time maximum. The result of this step is theestimated number of routes. In certain illustrative embodiments,performance of route number estimation from future anticipated demandcan include: (i) increase or decrease in volume (x %) to each customer(if you don't have forecasted volume locations, this is valid assumptionto apply volume increase; if anticipated seasonal loss of specificcustomers known use); (ii) find sequence for census tract (find optimalsequence of census tracts; exclude tracts if anticipate seasonal loss ofspecific existing customers is known); (iii) find sequence and calculateroute time for each census tract (find a sequence of stops in each tractby assuming previous tract's last stop as a starting point of thecurrent tract; route time estimation for tract does not consider LFtrips yet); and (iv) estimate number of routes based on route time androute/vehicle capacity (based on sequence of each tract, chop a longtrain of stops into a route, possibly heterogeneous, considering maxroute time, route capacity). This is based on assumption that existingcustomers have volume increase or loss of specific customers because ofseasonal changes by DOW, of 10%, in certain illustrative embodiments.

The presently disclosed system and method have a number of advantages.The estimation of routes is very accurate, since it considers landfill(“LF”) break points along with volume changes because of increase ordecrease of customers. Also, when volume estimation is known for certaingeographic units, such as tracts, changes can be added only in this areato impact the route change. This allows for what-if analysis to modeland estimate the number of routes based on the future customer demand.

The presently disclosed system and method can be especially effectivefor creation and maintenance of optimal and practical waste collectionroutes that meet operational realities (such as crossing highways,navigating physical boundaries, etc.) and enabling tactical planning.The number of routes in a given geographical area can be optimized torealize operational efficiencies and add new customers and/or serviceswhile still meeting existing customer commitments. Operational planningcan be improved, with users having the ability to estimate the number offuture routes based on future customer footprint or demand. Seasonalvolume changes can be considered, and customers can be put on hold toinform future routes. Future demand from customers can be incorporatedin a geographical area to enable the planning of waste collectionroutes. Estimating the number of future routes enables users to estimatefuture driver and vehicle needs to meet operational requirements.

FIGS. 2-3 and FIGS. 4-5 herein illustrate exemplary methods with aplurality of sequential, non-sequential, or sequence independent “steps”as described herein. It should be noted that the methods of FIGS. 2-3and FIGS. 4-5 are exemplary and may be performed in different ordersand/or sequences as dictated or described herein, and any alternativeembodiments thereof. Numerous arrangements of the various “steps” can beutilized. In addition, not all “steps” described herein need be utilizedin all embodiments. However, it should be noted that certain particulararrangements of “steps” for the methods described herein are materiallydistinguishable from and provide distinct advantages over previouslyknown technologies.

The presently disclosed system and method can be incorporated into thefunctional operations of the service vehicles, to communicate andprovide routing, optimization and other operational information tovehicle drivers and workers regarding waste/recycling collection anddelivery routes. This can occur prior to beginning operations and/or onan ongoing, real time basis. As a result, the disclosed subject matterhas a variety of practical applications, as well as provides solutionsto a number of technological and business problems of the prior art.

Service vehicles used in the waste collection, delivery, disposal andrecycling industry often have on-board computers, location devices andinterior and exterior safety and non-safety related cameras installed onthe exterior and interior thereof. These devices can provide wasteservices providers and their field managers with information related tothe service vehicle, location of the service vehicle, serviceconfirmation, customer service issues, service routing issues, customersite information and safety issues and concerns, as well as providevehicle drivers and workers with information relating to collection anddelivery routes.

For example, FIG. 6 is an example of a services environment 10 where thepresently disclosed system and method can be utilized. A service vehicle15 is configured to provide services to customers, which can includetypical lines of waste industry services such as waste collection andtransport and/or recycling for commercial, residential and/orindustrial. Service vehicle 15 collects waste or recyclables from aplurality of containers 20 which will typically be assigned to, orassociated with, specific customers registered to a waste collectioncompany.

FIG. 7 illustrates a high-level overview of a system and networkaccording to various illustrative embodiments herein. The components andgeneral architecture of the system and network may be adapted for use inthe specific services environment of FIG. 6. The system can include oneor more data sources 30 and a central server 35. Data sources 30 may be,for example, devices configured for capturing and communicatingoperational data indicative of one or more operational characteristics.Data sources 30 are configured to communicate with central server 35 bysending and receiving operational data over a network 45 (e.g., theInternet, an Intranet, or other suitable network). Central server 35 maybe configured to process and evaluate operational data received fromdata sources 30 in accordance with user input received via a userinterface provided on a local or remote computer.

In the illustrative embodiment shown in FIGS. 8-10, a system and networkare provided wherein a communications device 50 can be disposed on wasteservice vehicle 15. Communications device 50 and central server 35 areconfigured to communicate with each other via a communications network45 (e.g., the Internet, an Intranet, a cellular network, or othersuitable network). In addition, communications device 50 and centralserver 35 are configured for storing data to an accessible centralserver database 96 located on, or remotely from, central server 35. Inthe description provided herein, the system may be configured formanaging and evaluating the operation of a large fleet of servicevehicles 15. As such, in certain illustrative embodiments, the systemmay further comprise a plurality of communications devices 50, eachbeing associated with one of a plurality of waste service vehicles 15.

In certain illustrative embodiments, the communication betweencommunications device 50 provided on-board service vehicle 15 andcentral server 35 may be provided on a real time basis such that duringthe collection/delivery route, data is transmitted between each servicevehicle 15 and central server 35. Alternatively, communication device 50may be configured to temporarily store or cache data during the routeand transfer the data to the central server 35 on return of servicevehicle 15 to the location of the collection/delivery company.

In certain illustrative embodiments, as illustrated in FIG. 8, servicevehicle 15 can also include an onboard computer 60 and a location device65. Onboard computer 60 can be, for example, a standard desktop orlaptop personal computer (“PC”), or a computing apparatus that isphysically integrated with vehicle 15, and can include and/or utilizevarious standard interfaces that can be used to communicate withlocation device 65 and optical sensor 70. Onboard computer 60 can alsocommunicate with central server 35 via a communications network 45 viacommunication device 50. In certain illustrative embodiments, servicevehicle 15 can also include one or more optical sensors 70 such as videocameras and relating processors for gathering image and other data at ornear the customer site.

Location device 65 can be configured to determine the location ofservice vehicle 15 always while service vehicle 15 is inactive, inmotion and operating and performing service related and nonservicerelated activities. For example, location device 65 can be a GPS devicethat can communicate with the collection/delivery company. A satellite75 or other communications device can be utilized to facilitatecommunications. For example, location device 65 can transmit locationinformation, such as digital latitude and longitude, to onboard computer60 via satellite 75. Thus, location device 65 can identify the locationof service vehicle 15, and therefore the location of the customer sitewhere container 20 is located, after vehicle 15 has arrived at thecustomer site.

In the illustrative embodiment of FIGS. 9-10, an exemplary computersystem and associated communication network is shown. In certainillustrative embodiments, central server 35 can be configured to receiveand store operational data (e.g., data received from waste servicesvehicle 15) and evaluate the data to aid waste services company inimproving operational efficiency. Central server 35 can include variousmeans for performing one or more functions in accordance withembodiments of the present invention, including those more particularlyshown and described herein; however, central server 35 may includealternative devices for performing one or more like functions withoutdeparting from the spirit and scope of the present invention.

In certain illustrative embodiments, central server 35 can includestandard components such as processor 75 and user interface 80 forinputting and displaying data, such as a keyboard and mouse or a touchscreen, associated with a standard laptop or desktop computer. Centralserver 35 also includes a communication device 85 for wirelesscommunication with onboard computer 60.

Central server 35 may include software 90 that communicates with one ormore memory storage areas 95. Memory storage areas 95 can be, forexample, multiple data repositories which stores pre-recorded datapertaining to a plurality of customer accounts. Such information mayinclude customer location, route data, items expected to be removed fromthe customer site, and/or billing data. For example, using the location(e.g., street address, city, state, and zip code) of a customer site,software 90 may find the corresponding customer account in memorystorage areas 95. Database 96 for data storage can be in memory storagearea 95 and/or supplementary external storage devices as are well knownin the art.

While a “central server” is described herein, a person of ordinary skillin the art will recognize that embodiments of the present invention arenot limited to a client-server architecture and that the server need notbe centralized or limited to a single server, or similar network entityor mainframe computer system. Rather, the server and computing systemdescribed herein may refer to any combination of devices or entitiesadapted to perform the computing and networking functions, operations,and/or processes described herein without departing from the spirit andscope of embodiments of the present invention.

In certain illustrative embodiments, a system is provided for optimizingwaste/recycling collection and delivery routes for waste/recyclingservice vehicles. Central server 35 may utilize memory storage area 95and processor 75 in communication with memory storage area 95, and/oronboard computer 60 can be utilized, to perform the method stepsdescribed herein and communicate results to/from the vehicle, prior toand/or in real time during performance of the waste/recycling serviceactivity. Also, in certain illustrative embodiments, software canexecute the flow of the method steps of FIGS. 2-3 and FIGS. 4-5 hereinwhile interacting with the various system elements of FIGS. 6-10.

In certain illustrative embodiments, the presently disclosed systems andmethods can also be utilized in connection with a centralized platformfor remote, real-time customer management of waste/recycling pick-up andcollection services. In certain illustrative embodiments, a system forfacilitating selection and monitoring of waste/recycling pick-up andcollection services by a customer can include a memory, an electronicviewing portal with a display for viewing by a customer, and a processorcoupled to the memory programmed with executable instructions. Theprocessor and/or memory can be configured to receive identifyinginformation from a customer via the electronic viewing portal, associatethe customer with stored customer information based on the identifyinginformation, determine (using back end functionality) one or morewaste/recycling pick-up and collection service options for the customerbased on the stored customer information, which can include the use ofcustomer and/or container discovery information based on GPS drive pathanalysis for a waste/recycling service vehicle as described in thevarious embodiments herein, display the one or more waste/recyclingpick-up and collection service options on the display, receiveinstructions from the customer regarding which of the waste/recyclingpick-up and collection service options to perform, and display thestatus of the performance of the one or more waste/recycling pick-up andcollection service options on the electronic viewing portal for viewingby the customer. The customer facing applications may be present in theform of downloadable applications installable and executable on userdevices, e.g., “electronic viewing portals” such as computers,smartphones, or tablets. Additionally (or alternatively), the customerapplications may be available as one or more web applications,accessible via a client device having an internet browser. The customerfacing applications can utilize customer service digitalization andallow a customer to select and/or monitor waste/recycling pick-up andcollection services from the provider on a real-time basis, and thecustomer offerings can be based, in whole or in part, upon back endfunctionality that includes the use of customer and/or containerdiscovery information based on GPS drive path analysis for awaste/recycling service vehicle, as described in the various embodimentsherein. The presently disclosed systems and methods can also be utilizedin connection with a centralized platform for remote, real-time customermanagement of other services besides waste/recycling pick-up andcollection services, such as, for example, package delivery, logistics,transportation, food delivery, ride hailing, couriers, freighttransportation, etc.

Those skilled in the art will appreciate that certain portions of thesubject matter disclosed herein may be embodied as a method, dataprocessing system, or computer program product. Accordingly, theseportions of the subject matter disclosed herein may take the form of anentirely hardware embodiment, an entirely software embodiment, or anembodiment combining software and hardware. Furthermore, portions of thesubject matter disclosed herein may be a computer program product on acomputer-usable storage medium having computer readable program code onthe medium. Any suitable computer readable medium may be utilizedincluding hard disks, CD-ROMs, optical storage devices, or other storagedevices. Further, the subject matter described herein may be embodied assystems, methods, devices, or components. Accordingly, embodiments may,for example, take the form of hardware, software or any combinationthereof, and/or may exist as part of an overall system architecturewithin which the software will exist. The present detailed descriptionis, therefore, not intended to be taken in a limiting sense.

As used herein, the phrase “at least one of” preceding a series ofitems, with the terms “and” or “or” to separate any of the items,modifies the list as a whole, rather than each member of the list (i.e.,each item). The phrase “at least one of” allows a meaning that includesat least one of any one of the items, and/or at least one of anycombination of the items, and/or at least one of each of the items. Byway of example, the phrases “at least one of A, B, and C” or “at leastone of A, B, or C” each refer to only A, only B, or only C; anycombination of A, B, and C; and/or at least one of each of A, B, and C.As used herein, the term “A and/or B” means embodiments having element Aalone, element B alone, or elements A and B taken together.

While the disclosed subject matter has been described in detail inconnection with a number of embodiments, it is not limited to suchdisclosed embodiments. Rather, the disclosed subject matter can bemodified to incorporate any number of variations, alterations,substitutions or equivalent arrangements not heretofore described, butwhich are commensurate with the scope of the disclosed subject matter.

Additionally, while various embodiments of the disclosed subject matterhave been described, it is to be understood that aspects of thedisclosed subject matter may include only some of the describedembodiments. Accordingly, the disclosed subject matter is not to be seenas limited by the foregoing description, but is only limited by thescope of the claims.

What is claimed is:
 1. A method of optimizing delivery of waste orrecycling services to customers using a waste or recycling servicevehicle, the method comprising: developing, via a computing device, asequence of two or more census tracts containing customer stops usingUnited States census tract data, wherein developing the sequence of twoor more census tracts comprises determining a representing customer stopfor each census tract, wherein the representing stop comprises acustomer location that is at or near the centroid of the census tractand sequencing the census tracts using the representing stops of eachcensus tract to determine an optimal tract sequence list; developing,via the computing device, a travel route for the waste or recyclingservice vehicle using the sequence of two or more census tracts and aplurality of unrouted customer stops associated with the two or morecensus tracts; communicating the travel route to the waste or recyclingservice vehicle; and delivering waste or recycling services to customersalong the travel route with the waste or recycling service vehicle,wherein developing the travel route for the waste or recycling servicevehicle comprises: (i) adding all unrouted customer stops from eachcensus tract into the travel route, starting from the first census tractof the optimal tract sequence list, until the travel route has met adefined primary fullness criteria; (ii) removing all the added customerstops from the last census tract in (i) where the primary fullnesscriteria of the travel route has been met; (iii) adding all the unroutedcustomer stops from each census block group belonging to the last censustract in (i) into the travel route, starting from the first block groupof the census tract in (i) that is closest to the last census tract in(i) that fulfills the primary fullness criteria, until the travel routehas met a defined secondary fullness criteria; (iv) removing all theadded customer stops from the last census block group in (iii) where thesecondary fullness criteria of the travel route has been met; (v) addingall the unrouted customer stops from each census block belonging to thelast census block group in (iii) into the travel route, starting fromthe first block of the census block group in (iii) that is closest tothe census block group in (iii) that fulfills the primary fullnesscriteria, until the travel route has met a defined tertiary fullnesscriteria; (vi) determining an optimal sequence of customer stops for thetravel route; and (vii) repeating steps (i)-(vi) starting for the nextroute starting with the next census block in (v) or next census blockgroup in (iii) or next census tract in (i) depending on which step thefullness criteria is met, until the customer stops are optimallysequenced for the travel route; and (viii) repeating steps (i)-(vii)until all desired unrouted customer stops in each census tract arerouted.
 2. The method of claim 1, wherein the primary fullness criteriacomprises one or more of a daily volume capacity or a daily maximum timemet for the travel route.
 3. The method of claim 1, wherein thesecondary fullness criteria comprises one or more of a daily volumecapacity or a daily maximum time met for the travel route.
 4. The methodof claim 1, wherein the tertiary fullness criteria comprises one or moreof a daily volume capacity or a daily maximum time met for the travelroute.
 5. The method of claim 1, wherein the tertiary fullness criteriacan vary depending on the type of waste or recycling service vehicle. 6.The method of claim 2, wherein the primary fullness criteria furthercomprises real time route conditions, including but not limited totraffic conditions on the road, and wherein the position of the vehicleon the road through a GPS device can be applied to perform a real timereroute.
 7. The method of claim 2, wherein the primary fullness criteriafurther comprises one or more of the number of customers already served,and wherein the current customer being served relative to the remainingtime available to complete the route can be applied to perform a realtime reroute.
 8. The method of claim 3, wherein the secondary fullnesscriteria further comprises real time route conditions, including but notlimited to traffic conditions on the road, and wherein the position ofthe vehicle on the road through a GPS device can be applied to perform areal time reroute.
 9. The method of claim 3, wherein the secondaryfullness criteria further comprises one or more of the number ofcustomers already served, and wherein the current customer being servedrelative to the remaining time available to complete the route can beapplied to perform a real time reroute.
 10. The method of claim 4,wherein the tertiary fullness criteria further comprises real time routeconditions, including but not limited to traffic conditions on the road,and wherein the position of the vehicle on the road through a GPS devicecan be applied to perform a real time reroute.
 11. The method of claim4, wherein the tertiary fullness criteria further comprises one or moreof the number of customers already served, and wherein the currentcustomer being served relative to the remaining time available tocomplete the route can be applied to perform a real time reroute.
 12. Asystem for optimizing delivery of waste or recycling services tocustomers, the system comprising: a waste or recycling service vehicle;a memory storage area; and a processor in communication with the memorystorage area and configured to: develop a sequence of two or more censustracts containing customer stops using United States census tract data,wherein developing the sequence of two or more census tracts comprisesdetermining a representing customer stop for each census tract, whereinthe representing stop comprises a customer location that is at or nearthe centroid of the census tract and sequencing the census tracts usingthe representing stops of each census tract to determine an optimaltract sequence list, develop a travel route for the waste or recyclingservice vehicle using the sequence of two or more census tracts and aplurality of unrouted customer stops associated with the two or morecensus tracts, and communicate the travel route to the waste orrecycling service vehicle; wherein the processor is further configuredto (i) add all unrouted customer stops from each census tract into thetravel route, starting from the first census tract of the optimal tractsequence list, until the travel route has met a defined primary fullnesscriteria; (ii) remove all the added customer stops from the last censustract in (i) where the primary fullness criteria of the travel route hasbeen met; (iii) add all the unrouted customer stops from each censusblock group belonging to the last census tract in (i) into the travelroute, starting from the first block group of the census tract in (i)that is closest to the last census tract in (i) that fulfills theprimary fullness criteria, until the travel route has met a definedsecondary fullness criteria; (iv) remove all the added customer stopsfrom the last census block group in (iii) where the secondary fullnesscriteria of the travel route has been met; (v) add all the unroutedcustomer stops from each census block belonging to the last census blockgroup in (iii) into the travel route, starting from the first block ofthe census block group in (iii) that is closest to the census blockgroup in (iii) that fulfills the primary fullness criteria, until thetravel route has met a defined tertiary fullness criteria; (vi)determine an optimal sequence of customer stops for the travel route;(vii) repeat steps (i)-(vi) starting for the next route starting withthe next census block in (v) or next census block group in (iii) or nextcensus tract in (i) depending on which step the fullness criteria ismet, until the customer stops are optimally sequenced for the travelroute; and (viii) repeat steps (i)-(vii) until all desired unroutedcustomer stops in each census tract are routed.
 13. The system of claim12, wherein the processor is further configured to collect locationinformation for the vehicle as the vehicle travels along the travelroute and perform a real time reroute, and wherein the locationinformation is collected using a locating device capable of satellitecommunications with the vehicle.